Sequence indicators
Table of per sequence values of selected indicators.
seqindic(seqdata, indic=c("visited","trans","entr","cplx","turb2n"), with.missing=FALSE,
ipos.args=list(), prec.args=list(), w=1)seqdata |
a state sequence object (class |
indic |
vector of character strings. List of selected indicators among |
with.missing |
logical: should non-void missing values be treated as a regular state? If |
ipos.args |
list: when any of |
prec.args |
list: when |
w |
real in range [0,1]: when |
The number of visited states is the number of different elements in the sequence, e.g. 2 for aababba. The recurrence index 'recu' is the average number of visits of visited states, i.e. Dlgth/Visited, the number of spells on the number of visited states.
The sequence length, number of transitions, longitudinal entropy, volatility, duration standard deviation, complexity, turbulence, proportion of positive states, integrative potential, and precarity are computed respectively with functions seqlength, seqtransn, seqient, seqivolatility, seqivardur, seqici, seqST, seqipos, seqintegration, and seqprecarity. See corresponding help pages for details.
The proportion of positive states ('ppos') and the normative volatility ('nvolat') are the proportions of positive states in respectively the original sequences and the DSS. They ignore the value of dss in the ipos.args list.
The with.missing argument applies to all indicators but the length. 'lgth' returns the length obtained with with.missing=TRUE, and 'nonm' the length obtained with with.missing=FALSE.
A data frame with the selected indicators. Names are:
Lght: Length of the sequence
NonM: Number of non missing elements
Dlgth: Length of the sequence of distinct successive states (DSS)
Visited: Number of visited states
Recu: Average number of visits to visited states
Trans: Number of state changes
Transp: Number of state changes as a proportion of maximum number of transitions
Meand: Mean spell duration
Dustd: Duration standard deviation
Entr: Longitudinal entropy
Volat: Objective volatility
Nsubs: Number of subsequences of the DSS sequence
Cplx: Complexity
Turbn: Normalized turbulence
Turb: Turbulence
Ppos: Proportion of positive states
Nvolat: Normative volatility
Vpos: Volatility of positive-negative state sequences
Inpos: Integrative capacity
Prec: Precarity
Gilbert Ritschard
data(ex1)
sx <- seqdef(ex1[,1:13], right="DEL")
print(sx, format='SPS')
seqindic(sx, indic=c("lgth","nonm","visited","turbn","cplx"))
seqindic(sx, indic=c("lgth","nonm","visited","turbn","cplx"), with.missing=TRUE)
seqindic(sx, indic=c("lgth","dlgth","ppos","inpos","prec"), with.missing=TRUE,
ipos.args=list(pos.states=c("A","B")),
prec.args=list(state.order=c("A","B","C"), state.equiv=list(c("C","D"))))
seqindic(sx, indic=c("volat","binary"), ipos.args=list(pos.states=c("A","B")))
seqindic(sx, indic=c("basic","inpos"), ipos.args=list(pos.states="D"))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.